---
title: Agent with Storage
---

## Code

```python cookbook/models/ibm/watsonx/db.py
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.ibm import WatsonX
from agno.tools.duckduckgo import DuckDuckGoTools

# Setup the database
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db_url=db_url)

agent = Agent(
    model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"),
    db=db,
    tools=[DuckDuckGoTools()],
    add_history_to_context=True,
)
agent.print_response("How many people live in Canada?")
agent.print_response("What is their national anthem called?")
```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Set your API key">
    ```bash
    export IBM_WATSONX_API_KEY=xxx
    export IBM_WATSONX_PROJECT_ID=xxx
    ```
  </Step>

  <Step title="Install libraries">
    ```bash
    pip install -U ddgs psycopg sqlalchemy ibm-watsonx-ai agno
    ```
  </Step>

  <Step title="Set up PostgreSQL">
    Make sure you have a PostgreSQL database running. You can adjust the `db_url` in the code to match your database configuration.
  </Step>

  <Step title="Run Agent">
    <CodeGroup>
    ```bash Mac
    python cookbook/models/ibm/watsonx/db.py
    ```

    ```bash Windows
    python cookbook\models\ibm\watsonx\db.py
    ```
    </CodeGroup>
  </Step>
</Steps>

This example shows how to use PostgreSQL storage with IBM WatsonX to maintain conversation state across multiple interactions. It creates an agent with a PostgreSQL storage backend and sends multiple messages, with the conversation history being preserved between them.

Note: You need to install the `sqlalchemy` package and have a PostgreSQL database available.